Strategic analytics: towards fully embedding evidence in healthcare decision-making.

Cancer Care Ontario (CCO) has implemented multiple information technology solutions and collected health-system data to support its programs. There is now an opportunity to leverage these data and perform advanced end-to-end analytics that inform decisions around improving health-system performance. In 2014, CCO engaged in an extensive assessment of its current data capacity and capability, with the intent to drive increased use of data for evidence-based decision-making. The breadth and volume of data at CCO uniquely places the organization to contribute to not only system-wide operational reporting, but more advanced modelling of current and future state system management and planning. In 2012, CCO established a strategic analytics practice to assist the agency's programs contextualize and inform key business decisions and to provide support through innovative predictive analytics solutions. This paper describes the organizational structure, services and supporting operations that have enabled progress to date, and discusses the next steps towards the vision of embedding evidence fully into healthcare decision-making.

Diet patterns and the risk of renal cell carcinoma.

OBJECTIVES: Our objective was to identify food intake patterns that might be associated with the risk of renal cell carcinoma. DESIGN: A total of 461 cases (210 females, 251 males) were age frequency matched to population controls. Diet factors were created using factor analysis of 69 food items from a food-frequency questionnaire. These factors were modelled using logistic regression to identify those associated with renal cell carcinoma. SETTING: We investigated the role of diet in the aetiology of renal cell carcinoma using a population-based case--control study conducted in Ontario between 1995 and 1996. SUBJECTS: Cases were Ontario residents 20 to 74 years of age identified through review of pathology reports in the Ontario Cancer Registry. RESULTS: A 'dessert' diet factor was positively associated with disease for both sexes (odds ratio estimate (OR) for males = 3.7, 95% confidence interval (CI) 2.0-6.9; OR for females = 1.4, 95% CI 0.8-2.2, for the highest vs. lowest quartile). In males, a 'beef' diet factor was identified and was associated with an increased risk of renal cell carcinoma. Furthermore, a 'juices' diet factor also showed an association with increased risk in males (OR = 1.8, 95% CI 1.0-3.1). For females, a positive association was observed between renal cell carcinoma and an 'unhealthy' diet factor (OR = 1.4, 95% CI 0.8-2.4). CONCLUSIONS: Our findings confirmed that high-fat and high-protein diets might be risk factors for renal cell carcinoma. The data also suggest an increased risk associated with juice intake, a finding not previously reported.